Communicable, Maternal, Neonatal, and Nutritional Disease Burden (CMNN)

# Load necessary packages
pacman::p_load(tidyverse, 
               knitr, 
               here,
               dplyr,
               janitor,
               plotly)

# Import the communicable diseases data
data_cmnn <- read_csv(here("data", "burden-of-disease-cmnn.csv"))
## Rows: 8100 Columns: 4
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (2): Entity, Code
## dbl (2): Year, DALYs (Disability-Adjusted Life Years) - Communicable, matern...
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

Table of Estimates for CMNN Burden Over Time

# Here render a table for the DALY burden over time for the three countries
#clean row names and then filter the countries
data_cmnn_orig_eafrica <- 
data_cmnn %>% 
   clean_names() %>% 
    filter(entity %in% c("Uganda","Kenya","Tanzania")) %>% 
    dplyr::rename(cmnn_srate = 
             dal_ys_disability_adjusted_life_years_communicable_maternal_neonatal_and_nutritional_diseases_sex_both_age_age_standardized_rate,
             country= entity)
# You should pivot the data to show each country in a separate column.
data_cmnn_orig_eafrica_wide <- 
data_cmnn_orig_eafrica %>% 
select(!code) %>% 
pivot_wider(values_from = cmnn_srate,
            names_from = country
)
data_cmnn_orig_eafrica_wide
## # A tibble: 30 × 4
##     year  Kenya Tanzania Uganda
##    <dbl>  <dbl>    <dbl>  <dbl>
##  1  1990 34322.   51624. 75945.
##  2  1991 36630.   53380. 76978.
##  3  1992 39510.   55460. 77512.
##  4  1993 42581.   56854. 77695.
##  5  1994 45822.   58453. 76949.
##  6  1995 48346.   59609. 76070.
##  7  1996 50629.   60213. 74909.
##  8  1997 52614.   60717. 73727.
##  9  1998 53894.   60494. 72244.
## 10  1999 54448.   59438. 70524.
## # ℹ 20 more rows
# Use kable() from the knitr package to render the table.
tab_rendered <- 
knitr::kable(data_cmnn_orig_eafrica_wide)
tab_rendered
year Kenya Tanzania Uganda
1990 34321.93 51624.16 75944.97
1991 36629.81 53379.70 76978.02
1992 39510.43 55460.50 77511.61
1993 42581.44 56854.18 77695.11
1994 45822.47 58452.76 76948.73
1995 48345.59 59609.03 76070.29
1996 50629.20 60212.76 74909.36
1997 52614.39 60717.00 73726.62
1998 53893.87 60493.72 72243.52
1999 54448.17 59437.74 70524.46
2000 54031.62 58112.20 68550.38
2001 53562.06 56280.20 65942.75
2002 52740.17 54165.05 63032.73
2003 51644.87 51870.74 60345.84
2004 49622.21 49818.96 57778.01
2005 46850.49 47862.23 53612.07
2006 43667.25 45149.29 49145.64
2007 40418.84 41560.02 46258.95
2008 37667.66 38556.13 43621.19
2009 35177.11 36383.30 41071.17
2010 32880.90 34485.90 38831.56
2011 30877.60 32753.08 36196.78
2012 29278.72 30265.72 33312.56
2013 28096.14 27687.76 30292.27
2014 27007.80 26129.75 28099.68
2015 25610.50 24751.08 26900.48
2016 24209.18 23766.85 26645.55
2017 22982.12 22638.19 24668.12
2018 22034.76 21187.60 22896.94
2019 21312.06 20117.73 21904.64

Summary of CMNN Burden Findings

Provide a brief analysis based on the data presented in the table and chart. Highlight any significant findings or patterns. About 3 sentences.

DALYs for a disease or health condition are the sum of the years of life lost to due to premature mortality (YLLs) and the years lived with a disability (YLDs) due to prevalent cases of the disease or health condition in a population

  • According to the plot above, Uganda had slightly more years lost due to premature mortality due to the Communicable, Maternal, Neonatal, and Nutritional Disease Burden (CMNN) compared to its Kenyan and Tanzania counterparts in the East African Community

  • Additionaly life years lost have decreased over the years from 1990 to 2020

  • The data also shows that there was a notable disparity in the sum of years lost due to CMNN upto about 2005 among the three countries but with all countries registering steady decreases in the same and there being not notable variations for the next 15 years